IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 23 (12), page 1338-1350, 2001
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This paper presents the measurement of colored object reflectance, under different, general assumptions regarding the imaging conditions. We exploit the Gaussian scale-space paradigm for color images to define a framework for the robust measurement of object reflectance from color images. Object reflectance is derived from a physical reflectance model based on the Kubelka-Munk theory for colorant layers. Illumination and geometrical invariant properties are derived from the reflectance model. Invariance and discriminative power of the color invariants is experimentally investigated, showing the invariants to be successful in discounting shadow, illumination, highlights, and noise. Extensive experiments show the different invariants to be highly discriminative, while maintaining invariance properties. The presented framework for color measurement is well-founded in the physics of color as well as in measurement science. Hence the proposed invariants are considered more adequate for the measurement of invariant color features than existing methods.
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author = "Geusebroek, J. M. and van den Boomgaard, R. and Smeulders, A. W. M. and Geerts, H.",
title = "Color Invariance",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
number = "12",
volume = "23",
pages = "1338--1350",
year = "2001",
url = "http://www.science.uva.nl/research/publications/2001/GeusebroekTPAMI2001"